[argyllcms] Re: Argyll CMS in Fedora (and Mandriva)

  • From: "C" <ml-argyllcms712@xxxxxxxxxx>
  • To: argyllcms@xxxxxxxxxxxxx
  • Date: Fri, 21 Dec 2007 23:49:35 -0800

re: packaging ArgyllCMS for Fedora, et. al.,
I certainly hope that any difficulties to its addition can be overcome,
it'd be a great addition!

Also, somewhat (OT) but still relevant to CMS packaging
and complementary utilities, I think it'd also be great
to see LPROF and PHOTOPRINT packaged since then there'd
be several new CMS-aware tools available for Fedora
and so would synergize well with the capabilities of
ArgyllCMS, and other already existing packages like
Krita, Scribus, DigiKam, CinePaint, LCMS, et. al.

Perhaps even some kind of "CMS AWARE" RPM GROUP tag
or something could be added for packages that are
built with CMS support so it'd be easier for users
to locate and install them.

I wonder if there's any tool to implement
ICC aware transforms on spooled print jobs for
CUPS / Foomatic / Gutenprint.  It seems like one can
embed a ICC tag into files that are to be printed but
AFAIK there's nothing that actually does (as a print filter /
option) anything with that such as converting from source ICC
to printer colorspace.

q.v., both GPL, AFAIK:



Oh and back on the topic of ArgyllCMS and Fedora
packaging (compiler options), LINUX use, performance in general,
et. al.

I notice that some of ArgyllCMS's calculations can be a bit
CPU intensive.  I wonder if the following compilation options
could be of help in performance:

> New Targets and Target Specific Improvements
> IA-32/x86-64
> * -mtune=native and -march=native will produce code optimized for the host 
architecture as detected using the cpuid instruction.

> New Languages and Language specific improvements
> OpenMP is now supported for the C, C++ and Fortran compilers.

Actually I'm not quite sure about why that's listed; AFAIK OpenMP has 
(seemingly) been working
pretty well for a while in GCC, at least I've used it before in some programs.

It might be a relatively easy way to parallelize some of the compute intensive
tasks across multiple CPU cores without a lot of code development overhead, and
without breaking the compilation on compilers / CPUs that don't support
OpenMP or multi-cores.

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